metadata
license: mit
tags:
- generated_from_trainer
model-index:
- name: rubert-tiny2-srl
results: []
rubert-tiny2-srl
This model is a fine-tuned version of cointegrated/rubert-tiny2 on an unknown dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.4175
- eval_Benefactive_precision: 0.0
- eval_Benefactive_recall: 0.0
- eval_Benefactive_f1: 0.0
- eval_Benefactive_number: 5
- eval_Causator_precision: 0.0
- eval_Causator_recall: 0.0
- eval_Causator_f1: 0.0
- eval_Causator_number: 26
- eval_Cause_precision: 0.0
- eval_Cause_recall: 0.0
- eval_Cause_f1: 0.0
- eval_Cause_number: 21
- eval_ContrSubject_precision: 0.0
- eval_ContrSubject_recall: 0.0
- eval_ContrSubject_f1: 0.0
- eval_ContrSubject_number: 19
- eval_Deliberative_precision: 0.0
- eval_Deliberative_recall: 0.0
- eval_Deliberative_f1: 0.0
- eval_Deliberative_number: 10
- eval_Experiencer_precision: 0.5512
- eval_Experiencer_recall: 0.4321
- eval_Experiencer_f1: 0.4844
- eval_Experiencer_number: 162
- eval_Object_precision: 0.6905
- eval_Object_recall: 0.0963
- eval_Object_f1: 0.1691
- eval_Object_number: 301
- eval_Predicate_precision: 0.9360
- eval_Predicate_recall: 0.9737
- eval_Predicate_f1: 0.9545
- eval_Predicate_number: 571
- eval_overall_precision: 0.8585
- eval_overall_recall: 0.5874
- eval_overall_f1: 0.6976
- eval_overall_accuracy: 0.8855
- eval_runtime: 1.6021
- eval_samples_per_second: 355.786
- eval_steps_per_second: 355.786
- epoch: 1.0
- step: 4864
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1.1643470912014148e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 163748
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.28
- num_epochs: 5
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3